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Related Experiment Video

Updated: Mar 3, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Clinical records anonymisation and text extraction (CRATE): an open-source software system.

Rudolf N Cardinal1,2

  • 1Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Sir William Hardy Building, Downing Site, Cambridge, CB2 3EB, UK. rudolf@pobox.com.

BMC Medical Informatics and Decision Making
|April 27, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces CRATE, a free, open-source software for de-identifying electronic medical records. It enables secure research database creation and management, including patient consent for future studies.

Keywords:
AnonymisationClinical informaticsDe-identificationElectronic medical recordsOpen-source softwarePseudonymisationPsychiatry

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Area of Science:

  • Health Informatics
  • Medical Data Security
  • Bioinformatics

Background:

  • Electronic medical records (EMRs) contain valuable research data but include sensitive, identifiable patient information.
  • Sharing identifiable patient data outside clinical care requires explicit consent, limiting research accessibility.
  • Anonymization and de-identification techniques are crucial for enabling secondary research use of clinical data without compromising patient privacy.

Purpose of the Study:

  • To present CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system.
  • To demonstrate the feasibility of creating and managing research databases from sensitive clinical records.
  • To facilitate patient consent for research participation.

Main Methods:

  • Utilized separable functions for anonymizing/de-identifying relational databases.
  • Implemented secure cryptographic methods for mapping patient identifiers to research pseudonyms.
  • Integrated relational databases with external natural language processing tools and provided a web front end.
  • Supported a model for patient consent to be contacted about research.

Main Results:

  • CRATE achieves sensitivity and precision in de-identification comparable to existing systems.
  • The software securely maps patient identifiers to research pseudonyms using public cryptographic methods.
  • CRATE offers a web front end for research and administrative functions, including full-text indexing.
  • A specific consent-to-contact model is supported for patient engagement in research.

Conclusions:

  • Creating and managing research databases from sensitive clinical records is practical using CRATE.
  • Secure pseudonym generation, full-text indexing, and consent-to-contact processes are effectively supported.
  • The system is entirely free and open-source, promoting accessibility for research institutions.